Climate model projections suggest major North American biome shifts in response to anthropogenic climate change (Rehfeldt et al. 2012). Such shifts could have profound influences on native flora and fauna, many of which would have to move long distances to track their climatic niches. To evaluate potential ecosystem changes at a somewhat finer scale, I projected the change in climate space for level III ecoregions (Commission for Environmental Cooperation 1997) as surrogates for multiple associated species and ecological communities. First, I developed a random forest model (Breiman 2001) to predict ecoregion class from bioclimatic variables (Table 1), using 1-km interpolated climate data for the 1969-1990 normal period (Hamann et al. 2013), available at http://adaptwest.databasin.org.

R Code for this portion follows:

library(randomForest)
library(raster)

#eco = project directory
setwd(eco)
datlcc = read.csv("CECEcoregionSampleLCC.csv")
cececo = read.csv("CECecoregions.csv")
LCC <- CRS("+proj=lcc +lat_1=49 +lat_2=77 +lat_0=0 +lon_0=-95 +x_0=0 +y_0=0 +ellps=GRS80 +units=m +no_defs")

#cur = directory containing grids representing derived climate variables
setwd(cur)
clim <- list.files(cur, pattern =".asc$")
curclim<-stack(clim)
temp <- raster(clim[1])
ID <- as.data.frame(rasterToPoints(temp))
names(ID)[3] <- "ID4km"
ID$ID <- row.names(ID)
IDR <- raster(ncols=ncol(temp), nrows=nrow(temp), xmn=xmin(temp), xmx=xmax(temp), ymn=ymin(temp), ymx=ymax(temp))
IDRR <- rasterize(as.matrix(ID[,1:2]), IDR, as.numeric(ID[,4]))
curclim <- addLayer(curclim,IDRR)

setwd(eco)
sampleclim<-cbind(datlcc,extract(curclim,as.matrix(cbind(datlcc[,3],datlcc[,4]))))
sc <- na.omit(sampleclim)
names(sc)[ncol(sc)] <- "IDgrid"
sc$NA_L3CODE <- as.factor(as.character(sc$NA_L3CODE))
lu <- as.data.frame(levels(sc$NA_L3CODE))
lu$level <- row.names(lu)
names(lu)[1] <- "NA_L3CODE"
write.csv(lu,file="ecoregionlu.csv",row.names=FALSE)

eco.rf <- randomForest(y=sc$NA_L3CODE, x=sc[,5:(ncol(sc)-1)],importance = TRUE, proximity = TRUE, data=sc)
round(importance(eco.rf), 2)
varImpPlot(eco.rf) 
ecocurr <- predict(curclim,eco.rf)
projection(ecocurr) <- LCC
writeRaster(ecocurr,filename="currentlcc.tif",datatype='INT4S',format="GTiff",overwrite=TRUE)
curfreq <- freq(ecocurr)
ecolu <- merge(lu,curfreq,by.x="level",by.y="value")
names(ecolu)[3] <- "curr"

Table 1: Bioclimatic variables used as inputs to random forest models (from Hamann et al. 2013)

MAT: mean annual temperature (°C)
MWMT: mean temperature of the warmest month (°C)
MCMT: mean temperature of the coldest month (°C)
TD: difference between MCMT and MWMT, as a measure of continentality (°C)
MAP: mean annual precipitation (mm)
MSP: mean summer (May to Sep) precipitation (mm)
AHM: annual heat moisture index, calculated as (MAT+10)/(MAP/1000)
SHM: summer heat moisture index, calculated as MWMT/(MSP/1000)
DD0: degree-days below 0°C (chilling degree days)
DD5: degree-days above 5°C (growing degree days)
DD18: degree-days below 18°C
DD18: degree-days above 18°C
NFFD: the number of frost-free days
bFFP: the julian date on which the frost-free period begins
eFFP: the julian date on which the frost-free period ends
FFP: frost-free period
PAS: precipitation as snow (mm)
EMT: extreme minimum temperature over 30 years
EXT: extreme maximum temperature over 30 years
Eref: Hargreave’s reference evaporation
CMD: Hargreave’s climatic moisture index
RH: mean annual relative humidity (%)
Tavewt: winter (Dec to Feb) mean temperature (°C)
Tavesm: summer (Jun to Aug) mean temperature (°C)
PPTwt: winter (Dec to Feb) precipitation (mm)
PPTsm: summer (Jun to Aug) precipitation (mm)

This model was then used to project ecoregions onto future mid-century (2041-2070) and end-of-century (2071-2100) climate conditions. Climate projections were based on 1-km downscaled climate anomalies (Wang et al. 2016) generated by an ensemble of 15 widely-used GCMs from the Coupled Model Intercomparison Project, Phase 5 (CMIP5, Taylor et al. 2012), available at http://adaptwest.databasin.org. I used representative concentration pathway (RCP) 8.5, to represent the 21st century conditions that are to be expected without dramatic reductions in greenhouse gas emissions or technological fixes (Fuss et al. 2014). I also evaluated RCP 4.5 to represent a future in which significant emissions reductions are achieved.

The following code generates projections for each representative and time period:

fut = directory containing grids representing derived future climate variables
rcp <- c("rcp45","rcp85")
time <- c("2050s","2080s")
for (j in rcp) {
    for (k in time) {
            w  <- paste(fut,"NA_ENSEMBLE_",j,"_",k,"_Bioclim_ASCII/",sep="")
            setwd(w)
            futclim <- list.files(w,pattern=".asc$")
            s <-stack(futclim)
            p <- predict(s,eco.rf)
            projection(p) <- LCC
            futfreq <- as.data.frame(freq(p))
        names(futfreq)[2] <- paste(i,j,sep="_")
        ecolu <- merge(ecolu,futfreq,by.x="level",by.y="value")
            writeRaster(p, filename=paste(eco,"pred",j,k,sep="_"),datatype='INT4S',format="GTiff", overwrite=TRUE)
            }
    }

Results for RCP 4.5 and RCP 8.5 are shown in Figures 1 and 2, respectively:

Figure 1. Model-predicted (a) baseline, (b) mid-century, and (c) end-of-century changes in North American ecoregions for RCP 4.5. Boreal, hemi-boreal, and western forested regions are shown in green and blue-green shades; arctic ecoregions are in blue shades; prairie/parkland ecoregions are in brown shades; and temperate forest ecoregions are in yellow and orange shades (see Table 1 for full list of ecoregions). Boreal ecoregions are also outlined in black.

Figure 1. Model-predicted (a) baseline, (b) mid-century, and (c) end-of-century changes in North American ecoregions for RCP 4.5. Boreal, hemi-boreal, and western forested regions are shown in green and blue-green shades; arctic ecoregions are in blue shades; prairie/parkland ecoregions are in brown shades; and temperate forest ecoregions are in yellow and orange shades (see Table 1 for full list of ecoregions). Boreal ecoregions are also outlined in black.

Figure 2. Model-predicted (a) baseline, (b) mid-century, and (c) end-of-century changes in North American ecoregions for RCP 8.5. Boreal, hemi-boreal, and western forested regions are shown in green and blue-green shades; arctic ecoregions are in blue shades; prairie/parkland ecoregions are in brown shades; and temperate forest ecoregions are in yellow and orange shades (see Table 1 for full list of ecoregions). Boreal ecoregions are also outlined in black.

Figure 2. Model-predicted (a) baseline, (b) mid-century, and (c) end-of-century changes in North American ecoregions for RCP 8.5. Boreal, hemi-boreal, and western forested regions are shown in green and blue-green shades; arctic ecoregions are in blue shades; prairie/parkland ecoregions are in brown shades; and temperate forest ecoregions are in yellow and orange shades (see Table 1 for full list of ecoregions). Boreal ecoregions are also outlined in black.

Next, I used the following code to calculate the change in area (16 km2 pixels) for each Level III ecoregion (Table 2):

groups <- c("rcp45_2050s","rcp45_2080s","rcp85_2050s","rcp85_2080s")
setwd(eco)
for (i in groups) {
    g <- list.files(eco,pattern=i)
    g1 <- grep(pattern=".tif$",g,value=TRUE)
    m <- raster(g1)
    futfreq <- as.data.frame(freq(m))
    names(futfreq)[2] <- i
    ecolu <- merge(ecolu,futfreq,by.x="level",by.y="value")
    }
ecolu1 <- merge(unique(cececo[,c(2:4)]),ecolu[,2:7],by="NA_L3CODE")
write.csv(ecolu1,file="ecoregion_changesummary.csv",row.names=FALSE)

Table 2. Model-projected changes by ecoregion (sq km):

NA_L3CODE NA_L3NAME curr rcp45_2050s rcp45_2080s rcp85_2050s rcp85_2080s
1.1.2 Baffin and Torngat Mountains 147147 256752 278424 235507 106740
10.1.1 Thompson-Okanogan Plateau 79481 128181 102991 93853 17523
10.1.2 Columbia Plateau 87319 128349 130511 133438 92006
10.1.3 Northern Basin and Range 163503 52087 28000 26510 2500
10.1.4 Wyoming Basin 142375 20672 10308 8748 317
10.1.5 Central Basin and Range 248329 178117 161763 171074 44943
10.1.6 Colorado Plateaus 148135 410063 445829 458570 479993
10.1.7 Arizona/New Mexico Plateau 170714 215623 216068 215201 137227
10.1.8 Snake River Plain 71248 34098 22125 20400 1620
10.2.1 Mojave Basin and Range 145279 178168 214764 239676 559531
10.2.2 Sonoran Desert 249917 313014 308390 333780 477826
10.2.3 Baja Californian Desert 125247 108494 133306 143065 130262
10.2.4 Chihuahuan Desert 560769 634266 615488 614688 512968
11.1.1 California Coastal Sage, Chaparral, and Oak Woodlands 118844 119971 124429 124621 148146
11.1.2 Central California Valley 59912 55961 47599 41428 920
11.1.3 Southern and Baja California Pine-Oak Mountains 40794 52147 49068 48033 34558
12.1.1 Madrean Archipelago 119798 120764 113420 110430 109247
12.1.2 Piedmonts and Plains with Grasslands, Xeric Shrub, and Oak and Conifer Forests 225107 159305 140803 136965 67801
12.2.1 Hills and Interior Plains with Xeric Shrub and Mesquite Low Forest 117722 115409 104551 100841 60874
13.1.1 Arizona/New Mexico Mountains 119795 121932 125652 120830 138375
13.2.1 Sierra Madre Occidental with Conifer, Oak, and Mixed Forests 203850 129997 119021 106488 64358
13.3.1 Sierra Madre Oriental with Conifer, Oak, and Mixed Forests 99879 112527 125093 125837 102492
13.4.1 Interior Plains and Piedmonts with Grasslands and Xeric Shrub 30155 13136 9148 8526 1347
13.4.2 Hills and Sierras with Conifer, Oak, and Mixed Forests 90230 56118 46624 41800 21474
13.5.1 Sierras of Jalisco and Michoacan with Conifer, Oak, and Mixed Forests 45189 29437 30622 27347 19195
13.5.2 Sierras of Guerrero and Oaxaca with Conifer, Oak, and Mixed Forests 93219 56589 51279 46021 21458
13.6.1 Central American Sierra Madre with Conifer, Oak, and Mixed Forests 24543 10157 8224 8785 2653
13.6.2 Chiapas Highlands with Conifer, Oak, and Mixed Forest 47734 30717 26910 25142 11528
14.1.1 Coastal Plain with Low Tropical Deciduous Forest 45021 67157 58930 52306 26294
14.1.2 Hills and Sierra with Low Tropical Deciduous Forest and Oak Forest 32934 27023 22562 21273 9515
14.2.1 Northwestern Yucatan Plain with Low Tropical Deciduous Forest 21348 31181 43435 42619 120368
14.3.1 Sinaloa Coastal Plain with Low Thorn Tropical Forest and Wetlands 55351 184089 253772 303349 693883
14.3.2 Sinaloa and Sonora Hills and Canyons with Xeric Shrub and Low Tropical Deciduous Forest 116252 161186 188683 190719 386533
14.4.1 Balsas Depression with Low Tropical Deciduous Forest and Xerophytic Shrub 94443 142241 155449 167393 217971
14.4.2 Chiapas Depression with Low Deciduous and Medium Semi-Deciduous Tropical Forest 27227 13295 11191 10296 9580
14.4.3 Valleys and Depressions with Xeric Shrub and Low Tropical Deciduous Forest 27146 38202 36891 37294 35815
14.5.1 Tehuantepec Canyon and Plain with Low Tropical Deciduous Forest and Low Thorn Tropical Forest 19737 41575 43559 41086 52429
14.5.2 South Pacific Hills and Piedmonts with Low Tropical Deciduous Forest 66703 85395 99426 102297 119513
14.6.1 Los Cabos Plains and Hills with Low Tropical Deciduous Forest and Xeric Shrub 16353 42909 43769 41573 23672
14.6.2 La Laguna Mountains with Oak and Conifer Forest 2570 1344 1185 1126 501
15.1.1 Gulf of Mexico Coastal Plain with Wetlands and High Tropical Rain Forest 92436 160749 153390 154527 136595
15.1.2 Hills with Medium and High Evergreen Tropical Forest 106764 75092 81041 90784 119204
15.2.1 Plain with Low and Medium Deciduous Tropical Forest 63136 123240 125750 130375 93831
15.2.2 Plain with Medium and High Semi-Evergreen Tropical Forest 46630 34045 29748 22123 2786
15.2.3 Hills with High and Medium Semi-Evergreen Tropical Forest 78883 5709 6137 5979 6417
15.3.1 Los Tuxtlas Sierra with High Evergreen Tropical Forest 10762 2087 1633 1416 13724
15.4.1 Southern Florida Coastal Plain 38967 74884 83614 78635 40314
15.5.1 Nayarit and Sinaloa Plain with Low Thorn Tropical Forest 9738 2650 1532 1425 1651
15.5.2 Jalisco and Nayarit Hills and Plains with Medium Semi-Evergreen Tropical Forest 20266 42203 49771 52308 75866
15.6.1 Coastal Plain and Hills with High and Medium-High Evergreen Tropical Forest and Wetlands 20201 25035 18554 17797 7691
2.1.4 Lancaster and Borden Peninsula Plateaus 153401 100458 57518 52380 2
2.1.5 Foxe Uplands 359792 172936 212147 159876 76162
2.1.6 Baffin Uplands 148664 39067 32090 28237 22447
2.1.7 Gulf of Boothia and Foxe Basin Plains 147691 94997 44196 30062 4356
2.1.9 Banks Island and Amundsen Gulf Lowlands 160336 239188 224215 194489 15065
2.2.1 Arctic Coastal Plain 58756 95 2266 5255 22959
2.2.2 Arctic Foothills 123434 235933 305118 459436 119091
2.2.3 Subarctic Coastal Plains 100808 229447 323128 388110 1281925
2.2.4 Seward Peninsula 59337 156920 256979 281469 286106
2.2.5 Bristol Bay-Nushagak Lowlands 63649 106118 103595 106972 389553
2.2.6 Aleution Islands 12993 4767 2467 2058 1132
2.4.1 Amundsen Plains 285721 491512 345481 217998 44812
2.4.3 Central Ungava Peninsula and Ottawa and Belcher Islands 168795 136014 90049 83728 57559
3.1.1 Interior Forested Lowlands and Uplands 154744 214494 244642 302972 397504
3.1.2 Interior Bottomlands 147095 104970 89188 60760 24020
3.1.3 Yukon Flats 43564 57030 38887 47545 20218
3.2.1 Ogilvie Mountains 78032 84458 80561 67101 40699
3.3.2 Hay and Slave River Lowlands 273770 329298 260311 228498 88246
3.4.3 Smallwood Uplands 260456 72043 45379 31847 8018
3.4.4 Ungava Bay Basin and George Plateau 124658 16561 15184 14273 175
3.4.5 Coppermine River and Tazin Lake Uplands 247484 278724 261461 289089 3376
4.1.2 Hudson Bay and James Bay Lowlands 277767 56692 24743 18601 4711
5.1.1 Athabasca Plain and Churchill River Upland 261634 180539 172825 169140 61254
5.1.2 Lake Nipigon and Lac Seul Upland 217842 383191 334585 292786 77691
5.1.3 Central Laurentians and Mecatina Plateau 302052 319010 262655 245088 61726
5.1.4 Newfoundland Island 125291 159633 150097 145165 141949
5.1.5 Hayes River Upland and Big Trout Lake 264910 99563 68160 60244 1195
5.1.6 Abitibi Plains and Riviere Rupert Plateau 287990 145527 142434 111390 15384
5.2.1 Northern Lakes and Forests 297661 550438 693642 770212 567791
5.2.3 Algonquin/Southern Laurentians 350698 443628 423668 436081 460129
5.3.1 Northern Appalachian and Atlantic Maritime Highlands 213235 297005 324996 338882 484216
5.3.3 North Central Appalachians 40906 5581 6484 7114 15510
5.4.1 Mid-Boreal Uplands and Peace-Wabaska Lowlands 384861 384235 311499 240506 112622
5.4.2 Clear Hills and Western Alberta Upland 147911 76236 63250 52958 8624
5.4.3 Mid-Boreal Lowland and Interlake Plain 137275 232935 277233 324472 401337
6.1.1 Interior Highlands and Klondike Plateau 125183 86212 115739 128553 19129
6.1.2 Alaska Range 101281 86438 91774 95471 35952
6.1.3 Copper Plateau 25317 7840 1044 376 21
6.1.4 Wrangell and St. Elias Mountains 58813 35893 27452 23311 14394
6.1.5 Watson Highlands 215821 109456 57769 43653 6952
6.1.6 Yukon-Stikine Highlands/Boreal Mountains and Plateaus 162769 50965 43275 34939 23134
6.2.1 Skeena-Omineca-Central Canadian Rocky Mountains 146470 160853 135239 120210 50879
6.2.10 Middle Rockies 161078 55926 45646 40694 18262
6.2.11 Klamath Mountains 59290 100615 113637 116533 190016
6.2.12 Sierra Nevada 56436 44004 41467 40535 22943
6.2.13 Wasatch and Uinta Mountains 95639 85060 84545 82247 40683
6.2.14 Southern Rockies 146075 79895 64838 51395 25539
6.2.15 Idaho Batholith 74737 76608 70690 73617 53969
6.2.2 Chilcotin Ranges and Fraser Plateau 113621 7374 2090 1782 122
6.2.3 Columbia Mountains/Northern Rockies 161058 252240 264915 271050 274785
6.2.4 Canadian Rockies 106010 53214 33347 23701 3133
6.2.5 North Cascades 41160 35151 31590 30225 19980
6.2.6 Cypress Upland 22463 925 2326 3179 3527
6.2.7 Cascades 48106 30917 32153 30980 24273
6.2.8 Eastern Cascades Slopes and Foothills 76924 50858 39265 37516 10082
6.2.9 Blue Mountains 81264 122265 114078 110356 113839
7.1.1 Ahklun and Kilbuck Mountains 62628 210151 224034 200959 32945
7.1.2 Alaska Peninsula Mountains 54947 28924 27208 26629 22337
7.1.3 Cook Inlet 31714 258308 325196 360731 204427
7.1.4 Pacific Coastal Mountains 109324 110053 113038 112518 87051
7.1.5 Coastal Western Hemlock-Sitka Spruce Forests 96025 167783 176032 178428 163666
7.1.6 Pacific and Nass Ranges 99230 133991 150169 153362 154938
7.1.7 Strait of Georgia/Puget Lowland 48048 37542 41816 44456 80267
7.1.8 Coast Range 57502 111722 124460 125210 146726
7.1.9 Willamette Valley 19425 4945 3615 3925 12446
8.1.1 Eastern Great Lakes Lowlands 185396 399806 511228 563219 801293
8.1.10 Erie Drift Plain 54959 3115 593 373 182
8.1.2 Lake Erie Lowland 71512 71944 50905 53404 21297
8.1.3 Northern Allegheny Plateau 56906 1487 534 560 23971
8.1.4 North Central Hardwood Forests 107373 103169 108931 101597 237007
8.1.5 Driftless Area 56904 27122 6541 9722 56230
8.1.6 Southern Michigan/Northern Indiana Drift Plains 81430 23829 17145 13253 417
8.1.7 Northeastern Coastal Zone 61604 230818 254436 245976 200520
8.1.8 Acadian Plains and Hills 111308 40773 46764 37862 28274
8.1.9 Maritime Lowlands 46701 13691 12593 8969 8838
8.2.1 Southeastern Wisconsin Till Plains 41043 42756 43861 32257 90658
8.2.2 Huron/Erie Lake Plains 54469 85966 67329 61276 28067
8.2.3 Central Corn Belt Plains 92678 73997 100504 140394 250957
8.2.4 Eastern Corn Belt Plains 87010 39615 33682 36241 8857
8.3.1 Northern Piedmont 42573 170005 167343 153662 53715
8.3.2 Interior River Valleys and Hills 131437 373661 383500 408178 433738
8.3.3 Interior Plateau 145391 60581 57552 55578 50507
8.3.4 Piedmont 199405 24230 20990 15243 2166
8.3.5 Southeastern Plains 304687 9091 6755 7501 3549
8.3.6 Mississippi Valley Loess Plains 85927 13701 11629 9952 22612
8.3.7 South Central Plains 178978 701415 692767 704770 611455
8.3.8 East Central Texas Plains 62055 166974 215681 249240 433078
8.4.1 Ridge and Valley 85618 29098 16038 10560 2334
8.4.2 Central Appalachians 89927 51069 40889 44792 66604
8.4.3 Western Allegheny Plateau 83575 8479 4804 3360 15
8.4.4 Blue Ridge 51004 33856 35301 35072 66437
8.4.5 Ozark Highlands 109761 76718 42713 26546 1981
8.4.6 Boston Mountains 24203 60902 63537 39483 5440
8.4.7 Arkansas Valley 38145 140421 168122 184531 89087
8.4.8 Ouachita Mountains 30471 87982 86472 65818 32104
8.4.9 Southwestern Appalachians 61141 14531 10304 8422 5821
8.5.1 Middle Atlantic Coastal Plain 114545 16124 25858 17272 22159
8.5.2 Mississippi Alluvial Plain 149150 337261 334998 319597 370833
8.5.3 Southern Coastal Plain 186085 95570 86825 80677 60148
8.5.4 Atlantic Coastal Pine Barrens 20263 22794 35426 36084 99628
9.2.1 Aspen Parkland/Northern Glaciated Plains 318674 466186 519631 546675 837779
9.2.2 Lake Manitoba and Lake Agassiz Plain 106437 403991 440897 460192 452954
9.2.3 Western Corn Belt Plains 218212 262681 224934 223667 209025
9.2.4 Central Irregular Plains 134204 204341 223959 238121 321836
9.3.1 Northwestern Glaciated Plains 366518 251564 231664 245870 563860
9.3.3 Northwestern Great Plains 368298 448245 460729 457994 390148
9.3.4 Nebraska Sand Hills 82506 46 27 60 4846
9.4.1 High Plains 292621 434924 488715 495241 467915
9.4.2 Central Great Plains 272514 356382 397340 404906 632890
9.4.3 Southwestern Tablelands 239595 364196 362126 335141 293115
9.4.4 Flint Hills 48028 113851 146532 151212 154204
9.4.5 Cross Timbers 108973 104547 117198 141406 379103
9.4.6 Edwards Plateau 111195 113999 97552 80404 27236
9.4.7 Texas Blackland Prairies 65484 90892 78487 87808 204468
9.5.1 Western Gulf Coastal Plain 115252 270442 323841 345851 502966
9.6.1 Southern Texas Plains/Interior Plains and Hills with Xerophytic Shrub and Oak Forest 192562 253019 291794 296432 391367

I also specifically summarized changes for boreal ecoregions (4.1, 5.4, 5.1, 3.4, 3.3, 3.2, 3.1, and 6.1) (Table 3):

Table 3. Model-projected changes by boreal ecoregion (sq km):

NA_L3CODE NA_L3NAME curr rcp45_2050s rcp45_2080s rcp85_2050s rcp85_2080s
3.1.1 Interior Forested Lowlands and Uplands 154744 214494 244642 302972 397504
3.1.2 Interior Bottomlands 147095 104970 89188 60760 24020
3.1.3 Yukon Flats 43564 57030 38887 47545 20218
3.2.1 Ogilvie Mountains 78032 84458 80561 67101 40699
3.3.2 Hay and Slave River Lowlands 273770 329298 260311 228498 88246
3.4.3 Smallwood Uplands 260456 72043 45379 31847 8018
3.4.4 Ungava Bay Basin and George Plateau 124658 16561 15184 14273 175
3.4.5 Coppermine River and Tazin Lake Uplands 247484 278724 261461 289089 3376
4.1.2 Hudson Bay and James Bay Lowlands 277767 56692 24743 18601 4711
5.1.1 Athabasca Plain and Churchill River Upland 261634 180539 172825 169140 61254
5.1.2 Lake Nipigon and Lac Seul Upland 217842 383191 334585 292786 77691
5.1.3 Central Laurentians and Mecatina Plateau 302052 319010 262655 245088 61726
5.1.4 Newfoundland Island 125291 159633 150097 145165 141949
5.1.5 Hayes River Upland and Big Trout Lake 264910 99563 68160 60244 1195
5.1.6 Abitibi Plains and Riviere Rupert Plateau 287990 145527 142434 111390 15384
5.4.1 Mid-Boreal Uplands and Peace-Wabaska Lowlands 384861 384235 311499 240506 112622
5.4.2 Clear Hills and Western Alberta Upland 147911 76236 63250 52958 8624
5.4.3 Mid-Boreal Lowland and Interlake Plain 137275 232935 277233 324472 401337
6.1.1 Interior Highlands and Klondike Plateau 125183 86212 115739 128553 19129
6.1.2 Alaska Range 101281 86438 91774 95471 35952
6.1.3 Copper Plateau 25317 7840 1044 376 21
6.1.4 Wrangell and St. Elias Mountains 58813 35893 27452 23311 14394
6.1.5 Watson Highlands 215821 109456 57769 43653 6952
6.1.6 Yukon-Stikine Highlands/Boreal Mountains and Plateaus 162769 50965 43275 34939 23134

This translates into 14% and 42% losses of boreal climate space by 2041-2070 and 2071-2100, respectively, based on RCP 8.5; or 9% and 13% losses based on RCP 4.5

Change projections can be found at http://adaptwest.databasin.org.

References

Breiman, L. 2001. Random Forests. Machine Learning 45:5-32.

Commission for Environmental Cooperation. 1997. Ecological Regions of North America: Toward a Common Perspective, Montreal, Canada.

Fuss, S., J. G. Canadell, G. P. Peters, M. Tavoni, R. M. Andrew, P. Ciais, R. B. Jackson, C. D. Jones, F. Kraxner, N. Nakicenovic, C. Le Quere, M. R. Raupach, A. Sharifi, P. Smith, and Y. Yamagata. 2014. Betting on negative emissions. Nature Climate Change 4:850-853.

Hamann, A., T. Wang, D. L. Spittlehouse, and T. Q. Murdock. 2013. A comprehensive, high-resolution database of historical and projected climate surfaces for western North America. Bulletin of the American Meteorological Society 94:1307-1309.

Rehfeldt, G. E., N. L. Crookston, C. Sáenz-Romero, and E. M. Campbell. 2012. North American vegetation model for land-use planning in a changing climate: a solution to large classification problems. Ecological Applications 22:119-141.

Taylor, K. E., R. J. Stouffer, and G. A. Meehl. 2012. An Overview of CMIP5 and the Experiment Design. Bulletin of the American Meteorological Society 93:485-498.

Wang, T., A. Hamann, D. Spittlehouse, and C. Carroll. 2016. Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America. PLoS ONE 11:e0156720.